where \(a \in (0, 1)\)  and \(Z_t,\, W_t\)  are i.i.d. with mean zero. This sequence has zero autocorrelation function values. Thus it is white noise in the sense of But large \(|X_t|\)  implies likely large \(V_t\) , then likely large \(V_{t+1}\) , and likely large \(|X_{t+1}|\) . Thus the sequence \(X_1, X_2, \ldots \)  is not independent identically distributed. This model was introduced in [1]} (for continuous time); see also discussion in [2]}. Another example is the GARCH(1, 1), introduced in [3]}:
\(X_t = V_tZ_t,\quad V_t^2 = a + bX_{t-1}^2 + cV_{t-1}^2,\) 
